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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Exploring the effects of a nonhydrostatic dynamical core in high-resolution aquaplanet simulations

This study explores the impact of a nonhydrostatic dynamical core in high-resolution regional climate simulations using an aquaplanet framework. The Weather Research and Forecasting (WRF) model is used to conduct simulations with both hydrostatic (H) and nonhydrostatic (NH) solvers at horizontal grid spacings (?x) of 36, 12, and 4 km. The differences between the H and NH simulated precipitation (?P) are notable even at ?x = 12 km in the inter-tropical convergence zone and the transition region to the drier subtropics. At gray-zone grid spacing (12 km and 4 km) over the tropics, ?P is sensitive to whether a cumulus parameterization scheme is used or not. With an idealized Witch of Agnesi land mountain, differences in the precipitation and circulation (vertical velocity) between the H and NH simulations are significant even at ?x = 36 km in the tropics due largely to the strong feedbacks related to moist processes. The differences increase as the model grid spacing and mountain half width (a) are reduced, accompanied by a shift towards a more nonhydrostatic flow regime at a = 24 km. Latent heat release drastically enhances the differences between the NH and H simulations and extends the effect of nonhydrostatic dynamics to a broader region over the mountain and downstream over the tropics. Overall, differences exist between H and NH simulations even at resolutions between 12 and 36 km, but the differences are sensitive to the representations of moist physics and other features such as horizontal diffusion used in the WRF model.

nonhydrostatic dynamics, latent heating, nonhydros↗
DOE OSTI2021

Lithium Oxide Superionic Conductors Inspired by Garnet and NASICON Structures

Abstract The key component in lithium solid‐state batteries (SSBs) is the solid electrolyte composed of lithium superionic conductors (SICs). Lithium oxide SICs offer improved electrochemical and chemical stability compared with sulfides, and their recent advancements have largely been achieved using materials in the garnet‐ and NASICON (sodium superionic conductor)‐ structured families. In this work, using the ion‐conduction mechanisms in garnet and NASICON as inspiration, a common pattern of an “activated diffusion network” and three structural features that are beneficial for superionic conduction: a 3D percolation Li diffusion network, short distances between occupied Li sites, and the “homogeneity” of the transport path are identified. A high‐throughput computational screening is performed to search for new lithium oxide SICs that share these features. From this search, seven candidates are proposed exhibiting high room‐temperature ionic conductivity evaluated using ab initio molecular dynamics simulations. Their structural frameworks including spinel, oxy‐argyrodite, sodalite, and LiM(SeO 3 ) 2 present new opportunities for enriching the structural families of lithium oxide SICs.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Chapter 7: Learning Stable Local Volt/Var Controllers in Distribution Grids

This chapter describes a framework to synthesize provably stable local Volt/Var controllers for distributed energy resources (DERs) in power distribution grids (DGs). The goal is to control the reactive power injections of DERs to improve the system performance as quantified by a generic optimal reactive power flow (ORPF) problem. To achieve this, we jointly design for each DER the control function, which prescribes the reactive power update rule, and the equilibrium function, which approximates the ORPF solutions from local measurements of voltages and powers. We provide conditions on the equilibrium functions and the control parameters ensuring the stability of the closed-loop system. In particular, we discuss the trade-offs between each set of conditions accounting for practical considerations, like fully exploiting the DERs' generation capabilities and reducing the optimality gap. These conditions are then translated into learning constraints on the neural networks' parameters that are enforced in the training phase. We validate our framework with numerical simulations on the IEEE 37-bus network and through a comparison with an optimized version of standard piece wise linear control rules.

closed-loop asymptotic stability↗
DOE OSTI2019

Shape optimization under uncertainty for rotor blades of horizontal axis wind turbines

We present a computational framework for the shape optimization of a Horizontal-Axis Wind Turbine (HAWT) rotor blade under uncertainty. Our framework integrates aerodynamic simulations based on the blade element method which utilizes reduced order models of the blade structure and wind load with design sensitivity analysis and nonlinear programming. The wind velocity is modeled as a stochastic process to account for variations in time and space. An additional stochastic process accounts for uncertainties in the structural material properties. The uncertainty propagation is based on a non-intrusive polynomial chaos expansion that allows accurate estimation of stochastic performance metrics such as generated power and structural compliance. Sensitivities of cost and constraint functions with respect to shape parameters namely twist angles are computed with an efficient scheme to enable gradient based optimization. To demonstrate the effect of uncertainty, designs obtained from optimization under uncertainty are compared to those obtained from deterministic optimization.

42 ENGINEERING↗
DOE OSTI2026

Multiphysics simulation of TRISO fuel compacts and the effects of homogenization on silver release predictions

This work studies the impact of explicit and homogenized modeling approaches on the multiphysics simulation of TRistructural ISOtropic (TRISO) fuel compacts in prismatic High Temperature Gas Reactors (HTGRs) and the silver release predictions. TRISO fuel compacts exhibit complex double heterogeneity that significantly affects heat conduction, neutron transport, and fission products release. In this work, we use Cardinal, a multiphysics tool based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, to couple neutron transport and heat conduction. OpenMC is used for neutron transport and the MOOSE heat transfer module is used for the heat conduction. Then, we use BISON for the silver release predictions. Two different modeling approaches—explicit modeling of individual TRISO particles and homogenized representation using effective thermal properties—are compared at high TRISO packing fractions (20% and 40%) across varying power densities. Results demonstrate that homogenization significantly under-predicts peak temperatures, for the case of high power/TRISO, there is a difference of 83.73 K in the maximum temperature. Additionally, homogenization underestimates the silver release predictions compared to explicit modeling. Specifically, the temperature and power density differences lead to significant differences in silver release predictions. This work demonstrates the importance of accurately modeling heterogeneity of the TRISO particles to reliably predict fission product release and assess reactor safety margins.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Understanding Differences in Water Adsorption Isotherms: Structural Variations, Force Fields, and Monte Carlo Simulation Approaches

Accurate prediction of water adsorption in micro- and mesoporous materials with hydrophobic pores is essential for the design and characterization of advanced adsorbent materials for separation and energy applications. Here, we assess the reproducibility and consistency of water adsorption isotherms in two microporous all-silica MFI zeolite structures (MFI-K and MFI-O) using two different zeolite force fields and three simulation approaches: grand canonical Monte Carlo (GCMC), Gibbs ensemble Monte Carlo (GEMC), and transition matrix Monte Carlo (TMMC). We demonstrate that consistent treatment of the bulk fluid phase in GCMC and TMMC simulations is critical for reconciling isotherms across methods, and we construct simulation-based equations of state for the TIP4P water model to enable rigorous fugacity-to-pressure conversions. Large shifts in the isotherms are observed for two zeolite force fields developed using different parametrization strategies, with the GCS force field representing implicitly a defect-containing all-silica zeolite, whereas the TraPPE-zeo force field accurately represents an essentially defect-free all-silica zeolite. While water in the van Koningsveld structure of MFI exhibits a first-order phase transition and condensation-like step for adsorption near room temperature, water in the Olson structure of MFI displays continuous adsorption, attributed to differences in the adsorption free energy landscapes. Structural analysis reveals that small geometric variations, particularly Si–O–Si bond angles near the strongest adsorption sites, lead to these substantial differences in adsorption behavior. Furthermore, our results highlight the sensitivity of simulated water adsorption isotherms in hydrophobic frameworks to seemingly small differences in the framework structures, force field parametrization, and simulation approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Electron Transfer Pathways Facilitating U(VI) Reduction by Fe(II) on Al- vs Fe-Oxides

This study continues mechanistic development of heterogeneous electron transfer (ET) pathways at mineral surfaces in aquatic environments that enable the reduction U(VI) by surface-associated Fe(II). Using computational molecular simulation within the framework of Marcus Theory, our findings highlight the importance of the configurations and interaction of the electron donor and acceptor species with the substrate, with respect to influencing its electronic structure and thereby the ability of semiconducting minerals to facilitate ET. U(VI) reduction by surface-associated Fe(II) (adsorbed or structurally incorporated into the lattice) on an insulating, corundum (001) surface (α-Al2O3) occurs when proximal inner-sphere (IS) surface complexes are formed, such that ET occurs through a combination of direct exchange (i.e., Fe d- and U f-orbitals overlap through space) and superexchange via intervening surface oxygen atoms. U(VI) reduction by coadsorbed Fe(II) on the isostructural semiconducting hematite (α-Fe2O3) basal surface requires either their direct electronic interaction (e.g., IS complexation) or mediation of this interaction indirectly through the surface via an intrasurface pathway. Conceptually possible longer-range ET by charge-hopping through surface Fe atoms was investigated to determine whether this indirect pathway is competitive with direct ET. The calculations show that energy barriers are large for this conduction-based pathway; interfacial ET into the hematite surface is endothermic (+80.1 kJ/mol) and comprises the rate-limiting step (10–6 s–1). The presence of the IS adsorbates appears to weaken the electronic coupling between underlying Fe ions within the surface, resulting in slower intra-surface ET (10–5 s–1) than expected in the bulk basal plane. Our findings lay out first insights into donor-acceptor communication via a charge-hopping pathway through the surface for heterogeneous reduction of U(VI) by Fe(II) and help provide a basis for experimental interrogation of this important process at mineral-water interfaces.

Taylor, S. D.↗
DOE OSTI2018

Perturbed Input Ensemble Modeling With the Space Weather Modeling Framework

Abstract To assess the effect of uncertainties in solar wind driving on the predictions from the operational configuration of the Space Weather Modeling Framework, we have developed a nonparametric method for generating multiple possible realizations of the solar wind just upstream of the bow shock, based on observations near the first Lagrangian point. We have applied this method to the solar wind inputs at the upstream boundary of Space Weather Modeling Framework and have simulated the geomagnetic storm of 5 April 2010. We ran a 40‐member ensemble for this event and have used this ensemble to quantify the uncertainty in the predicted Sym‐H index and ground magnetic disturbances due to the uncertainty in the upstream boundary conditions. Both the ensemble mean and the unperturbed simulation tend to underpredict the magnitude of Sym‐H in the quiet interval before the storm and overpredict in the storm itself, consistent with previous work. The ensemble mean is a more accurate predictor of Sym‐H, improving the mean absolute error by nearly 2 nT for this interval and displaying a smaller bias. We also examine the uncertainty in predicted maxima in ground magnetic disturbances. The confidence intervals are typically narrow during periods where the predicted d B H /d t is low. The confidence intervals are often much wider where the median prediction is for enhanced d B H /d t . The ensemble also allows us to identify intervals of activity that cannot be explained by uncertainty in the solar wind driver, driving further model improvements. This work demonstrates the feasibility and importance of ensemble modeling for space weather applications.

58 GEOSCIENCES↗
DOE OSTI2026

Characterization of volcanic tuff pores pre- and post-underground nuclear detonation using ultra-small and small angle neutron scattering

The ability to accurately model the subsurface transport of radionuclides is fundamental to the remote detection and characterization of underground nuclear explosion (UNE) events. Developing more sophisticated transport models presents a significant opportunity to enhance monitoring capabilities, particularly in the reliable prediction of signature migration. Experimentally determined characterization of geologic materials associated with transport properties is the pertinent base information for such robust model development and calibration. Here, we report results from an unprecedented study demonstrating changes to the pore and fracture network structures in geological materials in response to UNEs over nanometer to micrometer length scales. Volcanic tuffs of five different lithological formations from pre- and post-UNE environments were collected from the Nevada National Security Site. Combined ultra-small and small-angle neutron scattering techniques were used to characterize the tuff pore structure. The results demonstrate measurable differences in the specific surface area and porosity of samples pre- and post-shot from texturally similar lithological formations, indicating that pore properties can serve as a direct physical signature of a UNE. The results also provide experimentally determined transport parameters in support of advanced model development through the integration of gas migration, hydrodynamic simulations, and geologic framework models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Charges on a suspended silicon nitride membrane under a high-energy electron beam

Thin silicon nitride (SiN x ) membranes are widely used in gas and liquid phase transmission electron microscopy (TEM) and as phase plates to enhance imaging contrast. SiN x contains trap sites for both positive and negative charges, which can be manipulated by high-energy electron irradiation, external potential biasing, or light exposure. Charge accumulation on the membrane can significantly affect in situ TEM processes, including chemical and electrochemical reactions, nanoparticle dynamics, and catalytic activity, or introduce unwanted phase shifts when used as a phase plate. Here, in this study, charge accumulation on suspended SiN x membranes was investigated using off-axis electron holography combined with model-free charge analysis, supported by custom finite element analysis (FEA) simulations. An average residual positive charge density of approximately 2.8 × 10 −4 C m −2 was measured. Localized and stable regions of both positive and negative charges were identified on the membrane. The global positive and localized positive/negative charges give rise to strong electric fields and electroosmotic slip velocities at the membrane surface, which are sufficient to induce non-Brownian particle behavior and directional fluid flow, offering a physical explanation for previously observed anomalies in particle dynamics, nucleation, and growth during gas and liquid phase TEM experiments. These results provide a benchmark for understanding charge behavior at SiNx interfaces in gas and liquid phase TEM. Furthermore, the FEA simulations establish a framework for future investigations into charge distribution, electrostatic potentials, and electrical double layers at solid–liquid interfaces, particularly in complex geometries and chemically dynamic environments.

Suspended silicon↗
DOE OSTI2016

Unphysical divergences in response theory

Here, transition densities between excited states are key for nonlinear theoretical spectroscopy and multi-state non-adiabatic molecular dynamics (NAMD) simulations. In the framework of response theory, these transition densities are accessible from poles of the quadratic response function. It was shown recently that the thus obtained transition densities within time-dependent Hartree-Fock (TDHF) and adiabatic time-dependent density functional theory (TDDFT) exhibit unphysical divergences when the difference in excitation energy of the two states of interest matches another excitation energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

MOOSE Reactor Module: An Open-Source Capability for Meshing Nuclear Reactor Geometries

The U.S. Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has developed numerous physics solvers utilizing the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) framework for multiphysics reactor analysis. These solvers require input finite element meshes representing the discretized spatial domain. Typically, reactor analysts turn to licensed tools for the creation of reactor geometry meshes. Recently, open-source functionality has been added to the MOOSE framework to mesh common reactor geometries and improve MOOSE-based nuclear reactor application user workflows. The new functionality is primarily contained in the new Reactor module of MOOSE and includes support for hexagonal pins, assemblies, and cores, extended Cartesian geometry support, options for modeling static and rotating control drums within a hexagonal assembly, core periphery triangulation, and automatic tagging of pin, assembly, plane, and depletion regions for easier post processing of physics results. A set of reactor geometry mesh builder objects further streamlines the construction of hexagonal and Cartesian cores and allows mapping of materials to regions during mesh generation. The meshes produced with the MOOSE Reactor module may be used directly within MOOSE-based applications or exported as Exodus II files for use in other finite element solvers. The tools have been demonstrated and verified using a variety of NEAMS physics solvers on a range of reactor applications, including a sodium-cooled fast reactor core analysis using Griffin, a fast reactor assembly thermal deformation analysis using MOOSE Tensor Mechanics, and a heat pipe–cooled microreactor coupled analysis using Griffin, Bison, and Sockeye. MOOSE’s Reactor module provides significant advantages compared to the use of external meshing tools when analyzing Cartesian and hexagonal reactor lattices using MOOSE-based applications: immediate accessibility (open-source) to the end user, low barrier to entry for new users, speed of mesh generation, volume preservation of meshed fuel pins, and simplification of analysis workflow when used in conjunction with MOOSE-based applications.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

High-Fidelity Multiphysics Modeling of a Heat Pipe Microreactor Using BlueCrab

Researchers who are actively developing nuclear microreactors are planning to employ innovative designs and features using traditional commercial modeling tools that may be inadequate for their design and licensing activities. The codes developed under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program provide flexibility in terms of geometry modeling and multiphysics coupling and are particularly well suited for modeling novel microreactor concepts. To test the maturity of these codes, this paper introduces a conceptual heat pipe microreactor (HP-MR) designed to gather various technologies of interest to microreactor developers such as control drums, heat pipes, and hydride moderators. Here, the objective of this effort is to demonstrate NEAMS tools capability to perform high-fidelity multiphysics simulations, using coupled neutronics (via the Griffin code), heat conduction (via the BISON code), heat pipe modeling (via the Sockeye code), and hydrogen redistribution in hydride metal moderator (via the SWIFT code). Codes are coupled in-memory through the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which permits flexible multiphysics data transfer schemes. The analysis confirmed two key aspects of the HP-MR concept: (1) its ability to follow the power load requested from the heat pipe and (2) its ability to avoid heat pipe cascading failure unless designed with high power close to operating failure limits of its heat pipes. The developed computational model was distributed publicly on the Virtual Test Bed for training purposes to accelerate adoption by industry and to provide a high-fidelity multiphysics solution for benchmarking against other tools. Additional multiphysics analyses including other transients and coupled physics were identified as necessary future work, together with a focus on validating multiphysics behavior against experiments.

Microreactor↗
DOE OSTI2020

Direct time-domain determination of electron-phonon coupling strengths in chromium

In this work, we report the results of an ultrafast, direct structural measurement of optically pumped phonons in a Cr thin film using ultrashort x-ray pulses from a free-electron laser. In addition to measuring and confirming the known long-wavelength dispersion relation of Cr along a particular acoustic branch, we are able to determine the relative phase of the phonons as they are generated. The Cr sample exhibits two generation mechanisms for the phonons: the releasing of a preexisting charge density wave at higher frequencies, and the creation of an acoustic strain pulse via laser heating that dominates at lower frequencies. Furthermore, for the latter mechanism, we are able to measure the frequency dependence of the time required to generate the phonons. To explain the observed magnitude and slope of the delays, we perform first-principles simulations in the framework of density functional perturbation theory and ab initio molecular dynamics to fit anharmonic phonon models. In conclusion, these results show that the wave-vector dependence of the electron-phonon coupling is the driving mechanism behind the delay times: Phase-space limitation leads to higher times near the zone center. The absolute magnitudes of the delay times measured are found to be much shorter than the equilibrium electron-phonon coupling times we compute, indicating that the coupling strength is greatly enhanced when the electronic system is out of equilibrium with the lattice, as has been seen in bismuth and other systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Scheduling of Collaborative Sequential Compressed Sensing Over Wide Spectrum Band

The cognitive radio (CR) technology holds promise to significantly increase spectrum availability and wireless network capacity. With more spectrum bands opened up for CR use, it is critical yet challenging to perform efficient wideband sensing. In this work, we propose an integrated sequential wideband sensing scheduling framework that concurrently exploits sequential detection and compressed sensing (CS) techniques for more accurate and lower-cost spectrum sensing. First, to ensure more timely detection without incurring high overhead involved in periodic recovery of CS signals, we propose smart scheduling of a CS-based sequential wideband detection scheme to effectively detect the PU activities in the wideband of interest. Second, to further help users under severe channel conditions identify the occupied sub-channels, we develop two collaborative strategies, namely, joint reconstruction of the signals among neighboring users and wideband sensing-map fusion. Third, to achieve robust wideband sensing, we propose the use of anomaly detection in our framework. Lastly, extensive simulations demonstrate that our approach outperforms peer schemes significantly in terms of sensing delay, accuracy and overhead.

42 ENGINEERING↗
DOE OSTI2016

Response of precipitation extremes to idealized global warming in an aqua-planet climate model: towards a robust projection across different horizontal resolutions

Current climate models produce quite heterogeneous projections for the responses of precipitation extremes to future climate change. To help understand the range of projections from multimodel ensembles, a series of idealized 'aquaplanet' Atmospheric General Circulation Model (AGCM) runs have been performed with the Community Atmosphere Model CAM3. These runs have been analysed to identify the effects of horizontal resolution on precipitation extreme projections under two simple global warming scenarios. We adopt the aquaplanet framework for our simulations to remove any sensitivity to the spatial resolution of external inputs and to focus on the roles of model physics and dynamics. Results show that a uniform increase of sea surface temperature (SST) and an increase of low-to-high latitude SST gradient both lead to increase of precipitation and precipitation extremes for most latitudes. The perturbed SSTs generally have stronger impacts on precipitation extremes than on mean precipitation. Horizontal model resolution strongly affects the global warming signals in the extreme precipitation in tropical and subtropical regions but not in high latitude regions. This study illustrates that the effects of horizontal resolution have to be taken into account to develop more robust projections of precipitation extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Temperature Field Reconstruction of Surfaces Heated Through Radiative Heat Transfer Using Convolutional Neural Networks

Microreactors could play a crucial role in decarbonizing our energy portfolio. However, their development and implementation come with specific challenges, particularly regarding cost. Due to their compact size and the harsh operational environment, collecting real-time data on reactor operation can be challenging. Many probe designs are unable to withstand extreme conditions (e.g., temperature, radiation) in the reactor. In this context, using convolutional neural networks (CNNs) can pave the way for developing a nonintrusive approach that relies solely on ex-core sensors. A well-trained physics-informed CNN can reconstruct the distribution of a given physical quantity over a domain using only a few sensors, allowing us to reconstruct the desired field distribution even in a limited space or complex geometries where a large array of sensors is impractical. In this work, we present the initial steps toward developing a real-time tool for monitoring the thermal behavior of nuclear reactor pressure vessels. Based on an experimental setup, a computational model using the Multiphysics Object-Oriented Simulation Environment (moose) framework was built, where the Ray Tracing and Heat Conduction modules were used to evaluate the temperature distribution over a convex metal surface heated through radiative heat transfer. This metal surface represents a section of a heated nuclear reactor vessel wall. The model also accounts for solid mechanics physics through the moose Solid Mechanics module. In situ experimental data, acquired from a Texas A&M facility, were used to validate the computational model. Part of the data generated by the moose model was used to train the convolutional neural network to reconstruct the vessel wall's outer surface temperature. The CNN generalization was then compared against the experimental and computational data.

Aldeia Machado, Luiz Carlos↗
DOE OSTI2017

Mastodon

MASTODON has the capability to model stochastic nonlinear soil-structure interaction (NLSSI) in a dynamic probabilistic risk assessment framework. The NLSSI simulations include structural dynamics, time integration, dynamic porous media flow, nonlinear hysteretic soil constitutive models, geometric nonlinearities (gapping, sliding, and uplift). MASTODON is also the MOOSE based master application for dynamic PRA of external hazards.

Coleman, JustinLeigh↗